Loading...
Loading...
Medical imaging (X-ray, CT, MRI), electronic health records, clinical trials, ECG/EEG, pathology
12,795 datasets
Global Healthsites Mapping Project provides a list of operating health facilities in Bosnia and Herzegovina. The dataset includes attributes such as facility name, nature, activities, and geographic coordinates. It was last updated on 2026-06-11.
CDC's National Healthcare Safety Network (NHSN) provides weekly aggregated counts on hospital capacity, occupancy, and admissions for COVID-19, influenza, and RSV. Data is reported by acute care and critical access hospitals across the United States, with historical records beginning in November 2024. Metrics are not updated after their initial weekly publication.
Five tertiary hospitals in Sichuan Province, China, contributed data from 280 patients who underwent laparoscopic myomectomy between January 2021 and June 2025. This multicenter retrospective study evaluates the effects of pelvic drainage and postoperative rectal misoprostol on short-term surgical outcomes. The dataset includes perioperative parameters such as operative time, blood loss, and recovery metrics extracted from electronic medical records.
A 9.5 KB Excel dataset contains total and incremental cost-effectiveness results for various medical referral pathways. The data is based on simulations of 1,000 patients using both base values and mean values from a probabilistic sensitivity analysis. It was authored by Wei Yoon Poh and last updated on May 28, 2026.
From 1 January to 31 December 2024, this dataset records predictors of hospitalization for 1,011 patients presenting to hospitals in Sorong City. It was authored by Tri Nugraha Susilawati and shared under a CC-BY-4.0 license. The data is stored in a 13.5 KB XLS file.
3,208 passively detected malaria cases from healthcare facilities in Sorong City, Indonesia, recorded over the 2024 calendar year. The dataset, authored by Tri Nugraha Susilawati, is structured to identify factors influencing patient attendance. It was last updated on the figshare platform in June 2026.
A 5.5 KB Excel file from figshare analyzes associations between eosinophil count trajectories and patient mortality. Wen-Chao Zhang authored this dataset, which was last updated on June 4, 2026. It likely contains tabular data for predicting 28-day and 1-year mortality following an acute myocardial infarction.
Camilla Bjelland published a dataset on figshare in June 2026 containing demographic information for healthcare workers in Liberia. The data was collected from participants in individual interviews. The dataset is 5.5 KB in size and is available under a CC-BY-4.0 license.
Amir Hossin Moradpour Dehnavi created a dataset on the thematic structure of barriers to participation and perceived ethical value of religious ceremonies among medical sciences students. The dataset is stored in an XLS file sized 13.5 KB and was last updated on June 4, 2026. It is shared under a CC-BY-4.0 license on figshare.
208 patient records with baseline characteristics for the EFSG and NEFG groups. The dataset was authored by Yanan Zhu and last updated on June 4, 2026. It is available as a 9.5 KB XLS file under a CC-BY-4.0 license.
Adverse Events (AEs) in Patients from Groups C, M1, and M2 in the Pilot Study. The dataset is a 5.5 KB XLS file published by Boxuan Xu on figshare under a CC-BY-4.0 license. It was last updated on June 4, 2026.
Cox regression analysis data examining the relationship between LGI and mortality in patients with Acute Kidney Injury (AKI). The dataset is provided by Xuejin Ye and was last updated on June 4, 2026. It is a small dataset, 9.5 KB in size, stored in an XLS file format.
Baseline characteristics for patients categorized by survival outcome in an original cohort study. The dataset is a 13.5 KB Excel file authored by Xuejin Ye and last updated on June 4, 2026. It is shared under a CC-BY-4.0 license on figshare.
A clinical dataset of term neonates admitted with birth asphyxia, focusing on the relationship between electrolyte imbalance and hospital stay duration. The dataset is 5.5 KB in size and was authored by Bahari Yusuf. It was last updated on June 4, 2026.
481 participants provided baseline and post-intervention data on socio-demographic, diabetes-related, behavioral, and anthropometric variables. The dataset, authored by Ashmita Karki and last updated in June 2026, measures primary outcomes using the EQ5D-3L, EQVAS, PHQ-9, and PSS-10 tools. A separate qualitative dataset contains focus group discussion data from 40 participants.
Baoshan Wang's dataset contains retrospective analysis of 1,578 adult patients undergoing umbilical hernia repair surgery at Beijing Chaoyang Hospital from 2012 to 2024. It includes patient demographics, clinical characteristics, surgical methods, and cost components, with a mean hospitalization cost of 32,218.17 CNY. The data was used to identify key determinants influencing hospitalization costs over a 13-year period.
7,750 saliva samples from 22 cohorts were analyzed to explore links between oral microbiota and disease. Qixiang Yuan's 2026 meta-analysis identified nine core microbes in healthy controls and built random forest models with high AUC scores (0.898ā1.0) for disease classification. This work validates saliva microbiota as a potential source for non-invasive diagnostic markers.
7,750 saliva samples from 22 cohorts were analyzed to explore links between oral microbiota and disease. A meta-analysis of public 16S rRNA data identified nine core microbes and built a multi-disease prediction model. The study, authored by Qixiang Yuan and updated in April 2026, validated the feasibility of using saliva microbiota and machine learning for non-invasive diagnostics.
A meta-analysis of public 16S saliva data by Qixiang Yuan, published on figshare in April 2026, integrates 7,750 samples from 22 cohorts sourced from PubMed between 2016 and 2024. Bioinformatics analyses using QIIME2 and Wekemo revealed community characteristics, identified nine core microbes in healthy controls, and built multi-disease prediction models. The study validated the feasibility of establishing healthy baselines via saliva microbiota and using machine learning for non-invasive diagnosis.
A meta-analysis of 16S saliva data from 22 cohorts comprising 7,750 samples collected between 2016 and 2024. Bioinformatics analyses identified nine core microbiota and constructed random forest models for disease prediction. The dataset was created by Qixiang Yuan and published on figshare.